Artificial Intelligence in Customer Service – Possibilities Beyond the Hype

Imagine the benefit your business could achieve if every customer interaction was intelligent? Artificially intelligent?

Yes. The era of Artificial Intelligence (AI) has dawned upon us. From personal assistants on our smartphones to bring the keyword at boardroom meetings, AI is now ubiquitous.. But, what makes AI a beeline for personalized customer support?

In its essence, AI is a constellation of technologies. It is made up of several subsets including machine learning, natural language processing, image recognition, text analysis, sentiment analysis, and visual recognition, among many others.

This constellation of cognitive capabilities helps AI transform the way a business can deliver customer service. It can fire up a new way of personalized customer interaction that puts intelligence, creativity, and context-driven conversations to work. And the fact that it puts human intelligence to work with machine memory, speed, and precision makes it a perfect way to render personalized customer support.

It is no surprise that global brands like Alibaba, Lexus, and Uber use a combination of human and AI systems to deliver personalized customer support.

Let’s go few layers deeper to understand how AI is disrupting customer service with its intelligence.

Connecting the Dots

AI connects the dots of real-time data to arrive at proactive recommendations about the future. Let me give you an example. Imagine you have an AI system- a chatbot or a similar recommender system. If data from your CRM system can be fed into the AI system, it can correlate data points to find relationships between customer data sets.

Information  that such an AI system can unearth includes:

– What are the most common queries that first-time users have?
– What kind of queries frequent during a particular season?
– Is there a specific segment of users who ask questions?
– Can the users be identified personally for proactive suggestions?

Connecting the dots from datasets can help create canned responses that can drive proactive customer support, which brings us to the next point.

Personalized Conversations

There is one trait that remains constant across all types and ages of customers. Everybody likes to be addressed by their names, in the right way.

The sheer act of addressing a customer by name in chat support or in an email can drastically increase the bond your customers share with your brand. It is perhaps the basic way to deliver personalized customer support.

AI-powered chatbots are masters of this art. They can pick up customer information from CRM databases instantly to address customer at a personal level. Depending on the scale of automation, chatbots can even deliver context-driven conversations based on the recent progress of the customer journey.

To give a fictional example, a travel assistant chatbot can serve a customer with a message, “Hey Chandler, your flight is at 5 AM. Do you need a wakeup call?”

While context-driven conversations drive in-the-moment personalized customer support, proactive customer support can raise the bar higher.

Proactive Customer Support

Until AI took over the center stage, data analytics was the warcry for enterprises. It helped enterprises to pick needle-like insights from heaps of data. But, data analytics had a pebble in the shoe. It was reactive in nature. It looked into historical data and informed businesses about the cause and effect relationship of past incidents.

AI, on the other hand, is proactive in nature. It learns from historical data and prepares to resolve issues before they arrive. It alerts the stakeholders of issues so that they can be better prepared to address them.

Here are some ways AI systems can deliver proactive customer support:

– Determine when human assistance is needed and escalate the conversation to an agent
– Use speech analysis and sentiment analysis to prioritize customer service
– Give proactive service suggestions based on past purchase habits
– Offer customized IVR menu options that will route customers to agents quickly

The end result? There is minimal friction in providing customer support. Ultimately, this results in reduced complaints and customer churn.

In fact, China Merchant Bank has been using a front-end bot powered by WeChat messenger to handle 99.5% of customer queries. AI’s cognitive capabilities makes it possible to automate the responses to most of these queries with 99.8% accuracy.

One-time Investment, Long-term Benefits

Agent-driven manual customer service is great in many ways. Well-trained, professional, and empathetic agents can make a world of a difference. But it has certain shortfalls.

For example, it is expensive to hire, train, and sustain an agent as an employee. Also, the quality of service could vary from agent to agent. There is also the case of diminishing productivity during peak hours or holiday seasons. Add to that the ancillary costs of holidays, restricted business hours, recesses, and so on.

Compared to that, AI is a one-time investment that will derive value for the long-term. It can run round the clock, 365 days a year, except for negligible downtimes caused due to network issues. Even that can be ironed out with a backup connectivity infrastructure.

As an icing on the cake, AI systems can be integrated with multiple support channels. They can be integrated with social media, live chat, email, etc.

This makes omnichannel customer support reality and not a possibility. Customers, irrespective of which channel they approach for service, will receive a consistent and personalized support experience.

What Lies Ahead

“AI is more profound than electricity or fire”, said Google CEO Sundar Pichai at a town hall event in January 2016. Fast forward to 2018, AI has already pitched its stake as an intelligent partner in every business function.

Customer service is one function where it can leave a positive influence. AI systems will help reduce the burden of taking too many repetitive customer queries day in and day out.

Its cognitive capabilities including speech analysis, sentiment analysis, and much more will help drive contextual conversations that will result in superior customer experience. In short, AI-powered customer support is the future of customer support.